Features analysis for identification of date and party hubs in protein interaction network of Saccharomyces Cerevisiae

<p>Abstract</p> <p>Background</p> <p>It has been understood that biological networks have modular organizations which are the sources of their observed complexity. Analysis of networks and motifs has shown that two types of hubs, party hubs and date hubs, are responsible for this complexity. Party hubs are local coordinators because of their high co-expressions with their partners, whereas date hubs display low co-expressions and are assumed as global connectors. However there is no mutual agreement on these concepts in related literature with different studies reporting their results on different data sets. We investigated whether there is a relation between the biological features of <it>Saccharomyces Cerevisiae</it>'s proteins and their roles as non-hubs, intermediately connected, party hubs, and date hubs. We propose a classifier that separates these four classes.</p> <p>Results</p> <p>We extracted different biological characteristics including amino acid sequences, domain contents, repeated domains, functional categories, biological processes, cellular compartments, disordered regions, and position specific scoring matrix from various sources. Several classifiers are examined and the best feature-sets based on average correct classification rate and correlation coefficients of the results are selected. We show that fusion of five feature-sets including domains, Position Specific Scoring Matrix-400, cellular compartments level one, and composition pairs with two and one gaps provide the best discrimination with an average correct classification rate of 77%.</p> <p>Conclusions</p> <p>We study a variety of known biological feature-sets of the proteins and show that there is a relation between domains, Position Specific Scoring Matrix-400, cellular compartments level one, composition pairs with two and one gaps of <it>Saccharomyces Cerevisiae'</it>s proteins, and their roles in the protein interaction network as non-hubs, intermediately connected, party hubs and date hubs. This study also confirms the possibility of predicting non-hubs, party hubs and date hubs based on their biological features with acceptable accuracy. If such a hypothesis is correct for other species as well, similar methods can be applied to predict the roles of proteins in those species.</p

Orphan proteins of unknown function in the mitochondrial intermembrane space proteome: new pathways and metabolic cross-talk

The mitochondrial intermembrane space (IMS) is involved in protein transport, lipid homeostasis and metal ion exchange, while further acting in signalling pathways such as apoptosis. Regulation of these processes involves protein modifications, as well as stress-induced import or release of proteins and other signalling molecules. Even though the IMS is the smallest sub-compartment of mitochondria, its redox state seems to be tightly regulated. However, the way in which this compartment participates in the cross-talk between the multiple organelles and the cytosol is far from understood. Here we focus on newly identified IMS proteins that may represent future challenges in mitochondrial research. We present an overview of the import pathways, the recently discovered new components of the IMS proteome and how these relate to key aspects of cell signalling and progress made in stem cell and cancer research

A creature with a hundred waggly tails: intrinsically disordered proteins in the ribosome

This article is made available for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.Intrinsic disorder (i.e., lack of a unique 3-D structure) is a common phenomenon, and many biologically active proteins are disordered as a whole, or contain long disordered regions. These intrinsically disordered proteins/regions constitute a significant part of all proteomes, and their functional repertoire is complementary to functions of ordered proteins. In fact, intrinsic disorder represents an important driving force for many specific functions. An illustrative example of such disorder-centric functional class is RNA-binding proteins. In this study, we present the results of comprehensive bioinformatics analyses of the abundance and roles of intrinsic disorder in 3,411 ribosomal proteins from 32 species. We show that many ribosomal proteins are intrinsically disordered or hybrid proteins that contain ordered and disordered domains. Predicted globular domains of many ribosomal proteins contain noticeable regions of intrinsic disorder. We also show that disorder in ribosomal proteins has different characteristics compared to other proteins that interact with RNA and DNA including overall abundance, evolutionary conservation, and involvement in protein–protein interactions. Furthermore, intrinsic disorder is not only abundant in the ribosomal proteins, but we demonstrate that it is absolutely necessary for their various functions

Fungal Secretome Database: Integrated platform for annotation of fungal secretomes

<p>Abstract</p> <p>Background</p> <p>Fungi secrete various proteins that have diverse functions. Prediction of secretory proteins using only one program is unsatisfactory. To enhance prediction accuracy, we constructed Fungal Secretome Database (FSD).</p> <p>Description</p> <p>A three-layer hierarchical identification rule based on nine prediction programs was used to identify putative secretory proteins in 158 fungal/oomycete genomes (208,883 proteins, 15.21% of the total proteome). The presence of putative effectors containing known host targeting signals such as RXLX [EDQ] and RXLR was investigated, presenting the degree of bias along with the species. The FSD's user-friendly interface provides summaries of prediction results and diverse web-based analysis functions through Favorite, a personalized repository.</p> <p>Conclusions</p> <p>The FSD can serve as an integrated platform supporting researches on secretory proteins in the fungal kingdom. All data and functions described in this study can be accessed on the FSD web site at <url>http://fsd.snu.ac.kr/</url>.</p

Proteomic study of the membrane components of signalling cascades of Botrytis cinerea controlled by phosphorylation

Protein phosphorylation and membrane proteins play an important role in the infection of plants by phytopathogenic fungi, given their involvement in signal transduction cascades. Botrytis cinerea is a well-studied necrotrophic fungus taken as a model organism in fungal plant pathology, given its broad host range and adverse economic impact. To elucidate relevant events during infection, several proteomics analyses have been performed in B. cinerea, but they cover only 10% of the total proteins predicted in the genome database of this fungus. To increase coverage, we analysed by LC-MS/MS the first-reported overlapped proteome in phytopathogenic fungi, the “phosphomembranome” of B. cinerea, combining the two most important signal transduction subproteomes. Of the 1112 membrane-associated phosphoproteins identified, 64 and 243 were classified as exclusively identified or overexpressed under glucose and deproteinized tomato cell wall conditions, respectively. Seven proteins were found under both conditions, but these presented a specific phosphorylation pattern, so they were considered as exclusively identified or overexpressed proteins. From bioinformatics analysis, those differences in the membrane-associated phosphoproteins composition were associated with various processes, including pyruvate metabolism, unfolded protein response, oxidative stress response, autophagy and cell death. Our results suggest these proteins play a significant role in the B. cinerea pathogenic cycl

Studies of molecular mechanisms integrating carbon metabolism and growth in plants

Plants use light energy, carbon dioxide and water to produce sugars and other carbohydrates, which serve as stored energy reserves and as building blocks for biosynthetic reactions. Supply of light is variable and plants have evolved means to adjust their growth and development accordingly. An increasing body of evidence suggests that the basic mechanisms for sensing and signaling energy availability in eukaryotes are evolutionary conserved and thus shared between plants, animals and fungi. I have used different experimental approaches that take advantage of findings from other eukaryotes in studying carbon and energy metabolism in plants. In the first part, I developed a novel screening procedure in yeast aimed at isolating cDNAs from other organisms encoding proteins with a possible function in sugar sensing or signaling. The feasibility of the method was confirmed by the cloning of a cDNA from Arabidopsis thaliana encoding a new F-box protein named AtGrh1, which is related to the yeast Grr1 protein that is involved in glucose repression. In the second part of the study, plant homologues of key components in the yeast glucose repression pathway were cloned and characterized in the moss Physcomitrella patens, in which gene function can be studied by gene targeting. We first cloned PpHXK1 which was shown to encode a chloroplast localized hexokinase representing a previously overlooked class of plant hexokinases with an N-terminal chloroplast transit peptide. Significantly, PpHxk1 is the major hexokinase in Physcomitrella, accounting for 80% of the glucose phosphorylating activity. A knockout mutant deleted for PpHXK1 exhibits a complex phenotype affecting growth, development and sensitivities to plant hormones. I also cloned and characterized two closely related Physcomitrella genes, PpSNF1a and PpSNF1b, encoding type 1 Snf1-related kinases. A double knockout mutant for these genes was viable even though it lacks detectable Snf1-like kinase activity. The mutant suffers from pleiotropic phenotypes which may reflect a constitutive high energy growth mode. Significantly, the double mutant requires constant high light and is therefore unable to grow in a normal day/night light cycle. These findings are consistent with the proposed role of the Snf1-related kinases as energy gauges which are needed to recognize and respond to low energy conditions

A family of thermostable fungal cellulases created by structure-guided recombination

SCHEMA structure-guided recombination of 3 fungal class II cellobiohydrolases (CBH II cellulases) has yielded a collection of highly thermostable CBH II chimeras. Twenty-three of 48 genes sampled from the 6,561 possible chimeric sequences were secreted by the Saccharomyces cerevisiae heterologous host in catalytically active form. Five of these chimeras have half-lives of thermal inactivation at 63°C that are greater than the most stable parent, CBH II enzyme from the thermophilic fungus Humicola insolens, which suggests that this chimera collection contains hundreds of highly stable cellulases. Twenty-five new sequences were designed based on mathematical modeling of the thermostabilities for the first set of chimeras. Ten of these sequences were expressed in active form; all 10 retained more activity than H. insolens CBH II after incubation at 63°C. The total of 15 validated thermostable CBH II enzymes have high sequence diversity, differing from their closest natural homologs at up to 63 amino acid positions. Selected purified thermostable chimeras hydrolyzed phosphoric acid swollen cellulose at temperatures 7 to 15°C higher than the parent enzymes. These chimeras also hydrolyzed as much or more cellulose than the parent CBH II enzymes in long-time cellulose hydrolysis assays and had pH/activity profiles as broad, or broader than, the parent enzymes. Generating this group of diverse, thermostable fungal CBH II chimeras is the first step in building an inventory of stable cellulases from which optimized enzyme mixtures for biomass conversion can be formulated

Dissecting a complex chemical stress: chemogenomic profiling of plant hydrolysates.

The efficient production of biofuels from cellulosic feedstocks will require the efficient fermentation of the sugars in hydrolyzed plant material. Unfortunately, plant hydrolysates also contain many compounds that inhibit microbial growth and fermentation. We used DNA-barcoded mutant libraries to identify genes that are important for hydrolysate tolerance in both Zymomonas mobilis (44 genes) and Saccharomyces cerevisiae (99 genes). Overexpression of a Z. mobilis tolerance gene of unknown function (ZMO1875) improved its specific ethanol productivity 2.4-fold in the presence of miscanthus hydrolysate. However, a mixture of 37 hydrolysate-derived inhibitors was not sufficient to explain the fitness profile of plant hydrolysate. To deconstruct the fitness profile of hydrolysate, we profiled the 37 inhibitors against a library of Z. mobilis mutants and we modeled fitness in hydrolysate as a mixture of fitness in its components. By examining outliers in this model, we identified methylglyoxal as a previously unknown component of hydrolysate. Our work provides a general strategy to dissect how microbes respond to a complex chemical stress and should enable further engineering of hydrolysate tolerance

Structure-function mapping of a heptameric module in the nuclear pore complex.

The nuclear pore complex (NPC) is a multiprotein assembly that serves as the sole mediator of nucleocytoplasmic exchange in eukaryotic cells. In this paper, we use an integrative approach to determine the structure of an essential component of the yeast NPC, the ~600-kD heptameric Nup84 complex, to a precision of ~1.5 nm. The configuration of the subunit structures was determined by satisfaction of spatial restraints derived from a diverse set of negative-stain electron microscopy and protein domain-mapping data. Phenotypic data were mapped onto the complex, allowing us to identify regions that stabilize the NPC's interaction with the nuclear envelope membrane and connect the complex to the rest of the NPC. Our data allow us to suggest how the Nup84 complex is assembled into the NPC and propose a scenario for the evolution of the Nup84 complex through a series of gene duplication and loss events. This work demonstrates that integrative approaches based on low-resolution data of sufficient quality can generate functionally informative structures at intermediate resolution